Request-Driven Architecture

1. Overview

Request-driven architecture is a design approach where the system operates based on requests initiated by users or other systems. Each request triggers a response from the system, leading to actions being performed or data being retrieved.

Request Initiators: Clients or systems that send requests to the architecture.
Request Handlers: Components or services that process incoming requests, often triggering a chain of operations.
Response Generators: Subsystems responsible for crafting the response back to the request initiator after processing.

Synchronous: The initiator waits for a response as the request is processed.
Asynchronous: The request is processed independently of the response, suitable for processes that are non-blocking and can operate without immediate data return.

HTTP/HTTPS: Often used in web-based request-driven architectures.
REST APIs: A popular way to implement requests and responses in a structured format.
Web Services/GraphQL: Other methodologies to facilitate requests within applications.

Scalability: Systems can be scaled horizontally by adding more handlers as demand increases.
Modularity: Enables separation of concerns as different request types can be directed to specific handlers.
Flexibility: Easily integrates with various external systems, allowing for diverse data sources and functions.

Latency: Potential for delay in receiving responses, especially with complex requests.
State Management: May require complex state management if requests depend on previous interactions.
Error Handling: Robust systems must handle errors gracefully to ensure consistent performance.

In contrast to event-driven architecture, request-driven systems center around external stimuli triggering operations, whereas event-driven ones respond to internal events.
Load balancing techniques are crucial in request-driven systems to distribute incoming requests evenly and maintain performance.
Proper design of APIs and clear contract definitions are essential to reduce the likelihood of integration issues across different services.
Monitoring and logging are vital for debugging and analyzing request patterns to identify potential bottlenecks and optimize performance.